Custom Modelsplat_iosplat_android

If you're an experienced ML developer and ML Kit's pre-built models don't
meet your needs, you can use a custom
TensorFlow Lite model with
ML Kit.

Host your TensorFlow Lite models using Firebase or package them with your app.
Then, use the ML Kit SDK to perform inference using the best-available
version of your custom model.
If you host your model with Firebase, ML Kit automatically updates your users
with the latest version.

This is a beta release of ML Kit for Firebase. This
API might be changed in backward-incompatible ways and is not subject to any
SLA or deprecation policy.

Key capabilities

TensorFlow Lite model hosting

Host your models using Firebase to reduce your app's binary size and to
make sure your app is always using the most recent version available of
your model

On-device ML inference

Perform inference in an iOS or Android app by using the ML Kit SDK to
run your custom TensorFlow Lite model. The model can be bundled with the
app, hosted in the Cloud, or both.

Automatic model fallback

Specify multiple model sources; use a locally-stored model when the
Cloud-hosted model is unavailable

Automatic model updates

Configure the conditions under which your app automatically downloads
new versions of your model: when the user's device is idle, is charging,
or has a Wi-Fi connection

Implementation path

Train your TensorFlow model

Build and train a custom model using TensorFlow. Or, re-train an
existing model that solves a problem similar to what you want to achieve.
See the TensorFlow Lite
Developer Guide.

Convert the model to TensorFlow Lite

Convert your model from standard TensorFlow format to TensorFlow Lite by
freezing the graph, and then using the TensorFlow Optimizing Converter
(TOCO). See the TensorFlow Lite
Developer Guide.

Host your TensorFlow Lite model with Firebase

Optional: When you host your TensorFlow Lite model with Firebase and
include the ML Kit SDK in your app, ML Kit keeps your users up to
date with the latest version of your model. You can configure ML Kit to
automatically download model updates when the user's device is idle or
charging, or has a Wi-Fi connection.